ReviewCells2021
Cardiac Computed Tomography Radiomics for the Non-Invasive Assessment of Coronary Inflammation.
Review in Cells, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed.
- Diagnosis of coronary artery disease in patients with type 2 diabetes mellitus based on computed tomography and pericoronary adipose tissue radiomics: a retrospective cross-sectional study.Cardiovascular diabetology · 2023Trial
- Radiomics-driven prediction of postoperative infection risk in maxillofacial fractures: multidimensional risk factor analysis and model construction based on absorbable plate fixation.Clinical oral investigations · 2026Review
- AI-driven radiomics in vascular disease: a narrative review of image analysis and clinical translation.Cardiovascular diagnosis and therapy · 2026Review
- Radiomics of Pericoronary Adipose Tissue and CT-FFR to Predict Major Adverse Cardiovascular Events in Patients with T2DM Complicated by CAD.Journal of cardiovascular translational research · 2026Article
- Developing a Reproducible Radiomics Model for Diagnosis of Active Crohn's Disease on CT Enterography Across Annotation Variations and Acquisition Differences.Journal of imaging informatics in medicine · 2025Article
- Protocol and rationale of the Australian multicentre registry for serial cardiac computed tomography angiography (ARISTOCRAT): a prospective observational study of the natural history of pericoronary adipose tissue attenuation and radiomics.Cardiovascular diagnosis and therapy · 2024Article
- Pericoronary Adipose Tissue Radiomics from Coronary Computed Tomography Angiography Identifies Vulnerable Plaques.Bioengineering (Basel, Switzerland) · 2023Article
- A radiomics model based on aortic computed tomography angiography: the impact on predicting the prognosis of patients with aortic intramural hematoma (IMH).Quantitative imaging in medicine and surgery · 2023Article
- Screening of COVID-19 Based on GLCM Features from CT Images Using Machine Learning Classifiers.SN computer science · 2023Article
- Unravelling the role of macrophages in cardiovascular inflammation through imaging: a state-of-the-art review.European heart journal. Cardiovascular Imaging · 2022Review
- Automated Classification of Atherosclerotic Radiomics Features in Coronary Computed Tomography Angiography (CCTA).Diagnostics (Basel, Switzerland) · 2022Article
- Effectiveness evaluation of different feature extraction methods for classification of covid-19 from computed tomography images: A high accuracy classification study.Biomedical signal processing and control · 2022Article
- Ultrasound Radiomics Nomogram Integrating Three-Dimensional Features Based on Carotid Plaques to Evaluate Coronary Artery Disease.Diagnostics (Basel, Switzerland) · 2022Article
- Editorial: Atherosclerosis and functional imaging.Frontiers in cardiovascular medicine · 2022Article
- Feasibility of Constructing an Automatic Meniscus Injury Detection Model Based on Dual-Mode Magnetic Resonance Imaging (MRI) Radiomics of the Knee Joint.Computational and mathematical methods in medicine · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Radiomics, via the extraction of quantitative information from conventional radiologic images, can identify imperceptible imaging biomarkers that can advance the characterization of coronary plaques and the surrounding adipose tissue. Such an approach can unravel the underlying pathophysiology of atherosclerosis which has the potential to aid diagnostic, prognostic and, therapeutic decision making. Several studies have demonstrated that radiomic analysis can characterize coronary atherosclerotic plaques with a level of accuracy comparable, if not superior, to current conventional qualitative and quantitative image analysis. While there are many milestones still to be reached before radiomics can be integrated into current clinical practice, such techniques hold great promise for improving the imaging phenotyping of coronary artery disease.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.